An OperationDescriptor describing the "Dilate" operation.
Dilation for gray scale images can be charaterized by "slide, add and max",
while for binary images by "slide and set". As always, the kernel
is expected to come with a key position.

Dilation, unlike convolution and most neighborhood operations,
actually can grow the image region. But to conform with other
image neighborhood operations, the border pixels are set to 0.
For a 3 x 3 kernel with the key point at the center, there will
be a pixel wide 0 stripe around the border.

When applied to multi-band images the dilation operator processes
each band independently using the methodology which would be applied
to single band images of the same data type.

Gray scale dilation is a spatial operation that computes
each output sample by adding elements of a kernel to the samples
surrounding a particular source sample and taking the maximum.
A mathematical expression is:

For a kernel K with a key position (xKey,yKey), the dilation
of image I at (x,y) is given by:

max{ I(x-i, y-j) + K(xKey+i, yKey+j): some (i,j) restriction }
where the (i,j) restriction means:
all possible (i,j) so that both I(x-i,y-j) and K(xKey+i, yKey+j)
are defined, that is, these indices are in bounds.

Intuitively in 2D, the kernel is like
an umbrella and the key point is the handle. When the handle moves
all over the image surface, the upper outbounds of all the umbrella
positions is the dilation. Thus if you want the image to dilate in
the upper right direction, the following kernel would do with
the bold face key position.

0

0

50

0

50

0

0

0

0

Note also that zero kernel have effects on the dilation!
That is because of the "max" in the add and max process. Thus
a 3 x 1 zero kernel with the key position at the bottom of the kernel
dilates the image upwards.

After the kernel is rotated 180 degrees, Pseudo code for dilation operation
is as follows. Of course, you should provide the kernel in its
(unrotated) original form. Assuming the kernel K is of size M rows x N cols
and the key position is (xKey, yKey).

Binary Image Dilation
requires the kernel K to be binary, that is, have values 0 or 1
for all kernel entries.
Intuitively, starting from dst image being a duplicate of src,
binary dilation slides the kernel K to place the key position
at every non-zero point (x,y) in src image and set dst positions
under ones of K to 1.

After the kernel is rotated 180 degrees, the pseudo code for
dilation operation is as follows. (Of course, you should provide
the kernel in its original unrotated form.)

// binary dilation
for every dst pixel location (x,y){
dst[x][y] = src[x][y];
for (i = -xKey; i < M - xKey; i++){
for (j = -yKey; j < N - yKey; j++){
if(src[x+i,y+i]==1 && Key(xKey+i, yKey+j)==1){
dst[x][y] = 1; break;
}
}
}
}
It should be noted that this operation automatically adds a
value of Boolean.TRUE for the
JAI.KEY_REPLACE_INDEX_COLOR_MODEL to the given
configuration so that the operation is performed
on the pixel values instead of being performed on the indices into
the color map if the source(s) have an IndexColorModel.
This addition will take place only if a value for the
JAI.KEY_REPLACE_INDEX_COLOR_MODEL has not already been
provided by the user. Note that the configuration Map
is cloned before the new hint is added to it. The operation can be
smart about the value of the JAI.KEY_REPLACE_INDEX_COLOR_MODELRenderingHints, i.e. while the default value for the
JAI.KEY_REPLACE_INDEX_COLOR_MODEL is
Boolean.TRUE, in some cases the operator could set the
default.